Abstract [en]

Optimisation of a geodetic network is performed to provide its pre-set quality requirements. Today, this procedure is almost run with the aid of developed analytical approaches, where the human intervention in the process cycle is limited to defining the criteria. The existing complication of optimisation problem was terminated by classifying it into several stages. By performing these steps, we aim to design a network with the best datum, configuration and the observation weights, which meets the precision, reliability and cost criteria.

In this thesis, which is a compilation of four papers in scientific journals, we investigate the optimisation problem by developing some new methods in simulated and real applications.

On the first attempt, the impact of different constraints in using a bi-objective optimisation model is investigated in a simulated network. It is particularly prevalent among surveyors to encounter inconsistencies between the controlling constraints, such as precision, reliability and cost. To overcome this issue in optimisation, one can develop bi-objective or multi-objective models, where more criteria are considered in the object function. We found out that despite restricting the bi-objective model with precision and reliability constraints in this study, there is no significant difference in results compared to the unconstrained model. Nevertheless, the constrained models have strict controls on the precision of net points and observation reliabilities.

The importance of optimisation techniques in optimal design of displacement monitoring networks leads to the development of a new idea, where all the observations of two epochs are considered in the optimisation procedure. Traditionally, an observation plan is designed for a displacement network and repeated for the second epoch. In the alternative method, by using the Gauss-Helmert method, the variances of all observations are estimated instead of their weights to perform the optimisation. This method delivers two observation plans for the two epochs and provides the same displacement precision as the former approach, while it totally removes more observations from the plan.

To optimise a displacement monitoring network by considering a sensitivity criterion as a main factor in defining the capacity of a network in detecting displacements, a real case study is chosen. A GPS displacement monitoring network is established in the Lilla Edet municipality in the southwest of Sweden to investigate possible landslides. We optimised the existing monitoring network by considering all quality criteria, i.e. precision, reliability and cost to enable the network for detecting 5 mm displacement at the net points. The different optimisation models are performed on the network by assuming single baseline observations in each measurement session. A decrease of 17% in the number of observed baselines is yielded by the multi-objective model. The observation plan with fewer baselines saves cost, time and effort on the project, while it provides the demanded quality requirements.

The Lilla Edet monitoring network is also used to investigate the idea, where we assume more precise instruments in the second of two sequential epochs. In this study, we use a single-objective model of precision, and constrained it to reliability. The precision criterion is defined such that it provides the sensitivity of the network in detecting displacements and has a better variance-covariance matrix than at the first epoch. As the observations are GPS baselines, we assumed longer observation time in the second epoch to obtain higher precision. The results show that improving the observation precision in the second epoch yields an observation plan with less number of baselines in that epoch. In other words, separate observation plans with different configurations are designed for the monitoring network, considering better observation precision for the latter epoch.

Abstract [en]

One of the problems in the single-objective optimisation models (SOOMs) foroptimising geodetic networks is the contradiction of the controlling constraints, which maylead to their violation or infeasibility in the optimisation process. One way to solve thisproblem is to use a bi-objective optimisation model (BOOM) instead of SOOMs. In thispaper, we will use the BOOM of precision and reliability and investigate the influence ofthe controlling constraints in a two-dimensional simulated network. Our studies show thatthe unconstrained BOOM is a good model, which almost fulfils our precision and reliabilitydemands of the network. This model is also economical as more observables are removedfrom the plan whilst adding the controlling constraints leads to including more observables,which have no significant role.

Abstract [en]

In the traditional method of optimal design of displacement monitoring networks a higher precision, times better than the desired accuracy of displacements, is considered for the net points in such a way that the accuracy of the detected displacements meets the desired one. However, in this paper, we develop an alternative method by considering the total number of observations in two epochs without such a simple assumption and we call it two-epoch optimisation. This method is developed based on the Gauss-Helmert adjustment model and the variances of the observations are estimated instead of the weights to optimise the observation plan. This method can deliver the same results as the traditional one, but with less required observations in each epoch.

Abstract [en]

Since the year 2000, some periodic investigations have been performed in the Lilla Edet region to monitor and possibly determine the landslide of the area with the GPS measurements. The responsible consultant has conducted this project by setting up some stable stations for GPS receivers in the risky areas of Lilla Edet and measured the independent baselines amongst the stations according to their observation plan. Here, we optimise the existing surveying network and determine the optimal configuration of the observation plan based on different criteria. We aim to optimise the current network to become sensitive to detect 5 mm possible displacements in each net point. The network quality criteria of precision, reliability and cost are used as object functions to perform single-, bi- and multi-objective optimisation models. It has been shown in the results that the single-objective model of reliability, which is constrained to the precision, provides much higher precision than the defined criterion by preserving almost all of the observations. However, in this study, the multi-objective model can fulfil all the mentioned quality criteria of the network by 17% less measurements than the original observation plan, meaning 17% of saving time, cost and effort in the project.

Abstract [en]

In order to detect the geo-hazards, different deformation monitoring networks are usually established. It is of importance to design an optimal monitoring network to fulfil the requested precision and reliability of the network. Generally, the same observation plan is considered during different time intervals (epochs of observation). Here, we investigate the case that instrumental improvements in sense of precision are used in two successive epochs. As a case study, we perform the optimisation procedure on a GPS monitoring network around the Lilla Edet village in the southwest of Sweden. The network was designed for studying possible displacements caused by landslides. The numerical results show that the optimisation procedure yields an observation plan with significantly fewer baselines in the latter epoch, which leads to saving time and cost in the project. The precision improvement in the second epoch is tested in several steps for the Lilla Edet network. For instance, assuming two times better observation precision in the second epoch decreases the number of baselines from 215 in the first epoch to 143 in the second one.